Set-membership affine projection algorithm with variable data-reuse factor

This paper proposes a data-selective affine projection algorithm. The algorithm generalizes the ideas of the conventional set-membership affine-projection (SM-AP) algorithm to include a variable data-reuse factor. By utilizing the information provided by the data-dependent step size, we propose an assignment rule that automatically adjust the number of data reuses. A particular reduced-complexity implementation of the proposed algorithm is also considered in order to reduce the dimensions of the matrix inversions involved in the computation of update. Simulations show that a significant reduction in the overall complexity can be obtained with the algorithm as compared with the conventional SM-AP algorithm. In addition, the proposed algorithm retains the fast convergence of the conventional SM-AP algorithm, and the low steady-state error of the SM-NLMS algorithm